class_docstr: An ensemble that picks the "best" prediction and combines events from all.
  
  The following rules determine which prediction is the "best":
  1. "No user" predictions overrule all other predictions.
  
  2. End-to-end predictions overrule all other predictions based on
      user input - if and only if *no* "no user" prediction is present in the
      given ensemble.
  
  3. Given two predictions, if the maximum confidence of one prediction is
      strictly larger than that of the other, then the prediction with the
      strictly larger maximum confidence is considered to be "better".
      The priorities of the policies that made these predictions does not matter.
  
  4. Given two predictions of policies that are equally confident, the
      prediction of the policy with the higher priority is considered to be
      "better".
  
  Observe that this comparison is *not* symmetric if the priorities are allowed to
  coincide (i.e. if we cannot distinguish two predictions using 1.-4., then
  the first prediction is considered to be "better").
  
  The list of events in the final prediction will contain all mandatory
  events contained in the given predictions, the optional events given in the
  "best" prediction, and `DefinePrevUserUtteredFeaturization` event (if the
  prediction was made for a sequence of events ending with a user utterance).
docstr: Creates a new instance (see parent class for full docstring).
docstr_tok: ["Creates","a","new","instance","(","see","parent","class","for","full","docstring",")","."]
code: def create(
      cls,
      config: Dict[Text, Any],
      model_storage: ModelStorage,
      resource: Resource,
      execution_context: ExecutionContext,
  ) -> DefaultPolicyPredictionEnsemble:
      """Creates a new instance (see parent class for full docstring)."""
      return cls()
  
imports: from __future__ import annotations
  from abc import abstractmethod, ABC
  from typing import Optional, Text, List, Dict, Any
  import logging
  from rasa.engine.graph import GraphComponent
  from rasa.engine.storage.storage import ModelStorage
  from rasa.engine.storage.resource import Resource
  from rasa.engine.runner.interface import ExecutionContext
  from rasa.core.policies.policy import PolicyPrediction
  from rasa.shared.exceptions import RasaException, InvalidConfigException
  from rasa.shared.core.constants import ACTION_LISTEN_NAME
  from rasa.shared.core.domain import Domain
  from rasa.shared.core.events import ActionExecutionRejected, ActionExecuted, DefinePrevUserUtteredFeaturization
  from rasa.shared.core.trackers import DialogueStateTracker
label_desc: Use image node_id 1 for calling the DefaultPolicyPredictionEnsemble obj's underlying member method code with example usage: obj.create(cls, config, model_storage, resource, execution_context) and returns: cls